Abstract Vascular endothelial growth factor (VEGF) is a protein that has been implicated in protection against Alzheimer's disease (AD). High levels of cerebrospinal fluid (CSF) VEGF are associated with slower rates of cognitive decline and slower rates of brain atrophy. Furthermore, the neuroprotective effects of VEGF are particularly strong among individuals who are harboring high levels of AD neuropathology, suggesting VEGF may protect against the clinical consequences of AD. Indeed, when treating the hippocampus of AD mice with stem cells expression VEGF, the memory deficits associated with AD are reversed. Yet, the development of VEGF as a therapeutic target has been limited due to the large number of biological process impacted by VEGF signaling. The VEGF family consists of 5 ligand genes, 3 known tyrosine-kinase receptor genes, and 2 modulating receptor (neuropilins) genes. Interactions between this diverse set of ligands and receptors drive vastly different signaling cascades. Such biological variation provides an exciting opportunity to interrogate the various VEGF pathways through targeted genomics and proteomics. This proposal will seek to identify the VEGF signaling molecules that most strongly predict neuroprotection, and clarify the pathways that underly the beneficial effects of VEGF. We will leverage advanced genomic and proteomic approaches using human samples from well characterized longitudinal cohort studies of aging, with a particular focus on gene and protein expression in brain tissue. Our multi-disciplinary team is uniquely positioned to perform this detailed analysis of VEGF signaling by leveraging the Resilience from Alzheimer's Disease (RAD) database, which includes a harmonized and validated continuous metric of resilience across 8 large cohort studies of AD. In RAD, we have quantified the degree to which an individual is resilient to the cognitive deficits associated with AD neuropathology, providing the ideal phenotype to evaluate the effects of VEGF. The RAD includes genotype data (n=3037), gene expression data from brain tissue (n=588), and access to stored brain tissue for novel proteomic analyses (n=1433). This proposal will first perform a comprehensive analysis of VEGF ligand and receptor genes in brain tissue to identify which gene isoforms mostly strongly relate to resilience. Second, we will perform a detailed proteomic analysis in which we perform comprehensive measurement of all VEGF ligand and receptor proteoforms, including post-translational modifications, to clarify VEGF effects in brain at the protein level. Finally, we will leverage the rich VEGF signaling data generated from this proposal to identify additional genetic markers of resilience that fall along this same signaling pathway. Knowledge about the mechanisms, signaling pathways, and specific forms of VEGF that most strongly predict resilience will accelerate the development of VEGF signaling molecules as targets for pharmacological intervention.